GhostVision

🚧UNDER CONSTRUCTION🚧

Near-real time detection of derelict (ghost) crab pots with side-scan sonar.

Overview

GhostVision is an open-source Python interface for automatically detecting and mapping ghost (derelict) crab pots from side-scan sonar imagery. GhostVision leverages Yolo models trained with Roboflow. Detections are then georeferenced with PINGMapper.

Installation

GPU (Fast Inference)

GhostVision is optimized for running inference (predictions) on the GPU. The processing environment is installed with conda. Any flavor of conda will do, but we recommend Miniforge. Follow the instructions below based on your OS.

Windows Only

Windows does not natively support inference on the GPU. A utility called WSL (Windows Subsystem for Linux) needs to be installed in order to run inference on the GPU.

1. Install WSL (Windows Subsystem for Linux) &
2. Open the command prompt by launching Ubuntu from the Windows Start menu.

Install Miniforge

3. In a command prompt, download Miniforge with:

   wget "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh"
   

4. Install Miniforge with:

   bash Miniforge3-$(uname)-$(uname -m).sh
   

Install GhostVision

5. Install PINGInstaller:

   pip install pinginstaller
   

6. Install GhostVision:

   python -m pinginstaller ghostvision-gpu
   

CPU (Slow Inference; Experimental)

An experimental version of GhostVision is available to test inference speeds on the CPU. This has been tested on Windows 11 only.

1. Install Miniforge.
2. Open the Miniforge prompt.
3. Install PINGInstaller:

   pip install pinginstaller
   

4. Install GhostVision.

   python -m pinginstaller ghostvision
   

Usage

1. Open the appropriate command prompt based on your installation above.
2. Launch GhostVision:

   conda activate ghostvision
   python -m ghostvision
   

3. Select desired parameters and click Submit.

Download Custom Roboflow Object Detection Model

GhostVision includes Roboflow object detection models designed to detect crab pots from side-scan sonar imagery. You can train and use your own object detection model by downloading the model from Roboflow with the included utility.

1. Open the appropriate command prompt based on your installation above.
2. Launch the Roboflow model download utility:

   conda activate ghostvision
   python -m ghostvision rf-download
   

3. Supply your Roboflow API Key.
4. Enter the project name (all lowercase).
5. Enter the project version.

The model will be downloaded and available to use.

Acknowledgments

GhostVision has been made possible through mentorship, partnerships, financial support, open-source software, manuscripts, and documentation linked below.

NOTE: The contents of this repository are those of the author(s) and do not necessarily represent the views of the individuals and organizations specifically mentioned here.

Development Team: Cameron Bodine, Art Trembanis, Kleio Baxevani, Naveed Abbasi, Onur Bagoren, Olivia Hines, Jared Wierzbicki, Ophelia Christoph, Catherine Hughes, Julia Greco.

• Coastal Sediments, Hydrodynamics and Engineering Lab (CSHEL), College of Earth, Ocean, & Environment (CEOE), University of Delaware

• Project ABLE (Align, Build Leverage, and Expand)

• National Fish Trap, Removal, Assessent, and Prevention (TRAP) Program

• Delaware Sea Grant